Control of network activity through neuronal response modulation. - Christian D. Swinehart; Kris Bouchard; Peretz Partensky; L. F. Abbott (Neurocomputing, 2004)

Neural decoding of spoken vowels from human sensory-motor cortex with high-density electrocorticography. - Kristofer E. Bouchard; Edward F. Chang (EMBC, 2014)

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences. - Kristofer E. Bouchard; Surya Ganguli; Michael S. Brainard (Frontiers Comput. Neurosci., 2015)

An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition. - Jason D. Wittenbach; Kristofer E. Bouchard; Michael S. Brainard; Dezhe Z. Jin (PLoS Comput. Biol., 2015)

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data. - Sugeerth Murugesan; Kristofer E. Bouchard; Edward F. Chang; Max Dougherty; Bernd Hamann; Gunther H. Weber (BCB, 2016)

Usage Pattern-Driven Dynamic Data Layout Reorganization. - Houjun Tang; Surendra Byna; Steve Harenberg; Xiaocheng Zou; Wenzhao Zhang; Kesheng Wu; Bin Dong 002; Oliver Rübel; Kristofer E. Bouchard; Scott Klasky; Nagiza F. Samatova (CCGrid, 2016)

Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience. - Oliver Rübel; Max Dougherty; Prabhat; Peter Denes; David Conant; Edward F. Chang; Kristofer E. Bouchard (Frontiers Neuroinformatics, 2016)

Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex. - Kristofer E. Bouchard; Alejandro F. Bujan; Edward F. Chang; Friedrich T. Sommer (EMBC, 2017)

UoI-NMF Cluster: A Robust Nonnegative Matrix Factorization Algorithm for Improved Parts-Based Decomposition and Reconstruction of Noisy Data. - Shashanka Ubaru; Kesheng Wu; Kristofer E. Bouchard (ICMLA, 2017)

Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction. - Kristofer E. Bouchard; Alejandro F. Bujan; Farbod Roosta-Khorasani; Shashanka Ubaru; Prabhat; Antoine Snijders; Jian-Hua Mao; Edward F. Chang; Michael W. Mahoney; Sharmodeep Bhattacharyya (NIPS, 2017)

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions. - Sugeerth Murugesan; Kristofer E. Bouchard; Edward F. Chang; Max Dougherty; Bernd Hamann; Gunther H. Weber (BMC Bioinform., 2017)

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity. - Sugeerth Murugesan; Kristofer E. Bouchard; Jesse A. Brown; Bernd Hamann; William W. Seeley; Andrew Trujillo; Gunther H. Weber (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

International Neuroscience Initiatives through the Lens of High-Performance Computing. - Kristofer E. Bouchard; James B. Aimone; Miyoung Chun; Thomas Dean; Michael Denker; Markus Diesmann; David Donofrio; Loren M. Frank; Narayanan Kasthuri; Christof Koch; Oliver Rübel; Horst D. Simon; et al. (Computer, 2018)

Spiking Linear Dynamical Systems on Neuromorphic Hardware for Low-Power Brain-Machine Interfaces. - David G. Clark; Jesse A. Livezey; Edward F. Chang; Kristofer E. Bouchard (CoRR, 2018)

Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. - Anastasios Kyrillidis; Shashanka Ubaru; Georgios Kollias; Kristofer E. Bouchard (CoRR, 2018)

Optimizing the Union of Intersections LASSO (UoILASSO) and Vector Autoregressive (UoIVAR) Algorithms for Improved Statistical Estimation at Scale. - Mahesh Balasubramanian 001; Trevor D. Ruiz; Brandon Cook 001; Sharmodeep Bhattacharyya; Prabhat; Aviral Shrivastava; Kristofer E. Bouchard (CoRR, 2018)

HDMF: Hierarchical Data Modeling Framework for Modern Science Data Standards. - Andrew J. Tritt; Oliver Rübel; Benjamin K. Dichter; Ryan Ly; Donghe Kang; Edward F. Chang; Loren M. Frank; Kristofer E. Bouchard (IEEE BigData, 2019)

Laminar origin of evoked ECoG high-gamma activity. - Maximilian E. Dougherty; Anh P. Q. Nguyen; Vyassa L. Baratham; Kristofer E. Bouchard (EMBC, 2019)

Sparse, Predictive, and Interpretable Functional Connectomics with UoILasso. - Pratik S. Sachdeva; Sharmodeep Bhattacharyya; Kristofer E. Bouchard (EMBC, 2019)

Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis. - David G. Clark; Jesse Livezey; Kristofer E. Bouchard (NeurIPS, 2019)

Numerically Recovering the Critical Points of a Deep Linear Autoencoder. - Charles G. Frye; Neha S. Wadia; Michael Robert DeWeese; Kristofer E. Bouchard (CoRR, 2019)

Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Interrogating Learned Representations. - Jesse A. Livezey; Ahyeon Hwang; Kristofer E. Bouchard (CoRR, 2019)

PyUoI: The Union of Intersections Framework in Python. - Pratik S. Sachdeva; Jesse Livezey; Andrew J. Tritt; Kristofer E. Bouchard (J. Open Source Softw., 2019)

Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex. - Jesse A. Livezey; Kristofer E. Bouchard; Edward F. Chang (PLoS Comput. Biol., 2019)

Scaling of Union of Intersections for Inference of Granger Causal Networks from Observational Data. - Mahesh Balasubramanian 001; Trevor D. Ruiz; Brandon Cook 001; Prabhat; Sharmodeep Bhattacharyya; Aviral Shrivastava; Kristofer E. Bouchard (IPDPS, 2020)

Sparse and Low-bias Estimation of High Dimensional Vector Autoregressive Models. - Trevor D. Ruiz; Sharmodeep Bhattacharyya; Mahesh Balasubramanian 001; Kristofer E. Bouchard (L4DC, 2020)

State-based network similarity visualization. - Sugeerth Murugesan; Kristofer E. Bouchard; Jesse A. Brown; Mariam Kiran; Dan Lurie; Bernd Hamann; Gunther H. Weber (Inf. Vis., 2020)

The impact of reducing signal acquisition specifications on neuronal spike sorting. - John Hermiz; Elias Joseph; Kyu Hyun Lee; Isabella A. Baldacci; Jason E. Chung; Loren M. Frank; Kristofer E. Bouchard; Peter Denes (EMBC, 2021)

Collaborative Nonstationary Multivariate Gaussian Process Model. - Rui Meng; Herbie Lee; Kristofer E. Bouchard (CoRR, 2021)

Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model. - Rui Meng; Kristofer E. Bouchard (CoRR, 2021)

Learning from learning machines: a new generation of AI technology to meet the needs of science. - Luca Pion-Tonachini; Kristofer E. Bouchard; Héctor García Martín; Sean Peisert; W. Bradley Holtz; Anil Aswani; Dipankar Dwivedi; Haruko M. Wainwright; Ghanshyam Pilania; Benjamin Nachman; Babetta L. Marrone; Nicola Falco; et al. (CoRR, 2021)

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses. - Charles G. Frye; James Simon; Neha S. Wadia; Andrew Ligeralde; Michael Robert DeWeese; Kristofer E. Bouchard (Neural Comput., 2021)

Hangul Fonts Dataset: A Hierarchical and Compositional Dataset for Investigating Learned Representations. - Jesse A. Livezey; Ahyeon Hwang; Jacob Yeung; Kristofer E. Bouchard (ICIAP (3), 2022)

Time-series ML-regression on Graphcore IPU-M2000 and Nvidia A100. - Jan Balewski; Zhenying Liu; Alexander Tsyplikhin; Manuel Lopez Roland; Kristofer E. Bouchard (PMBS@SC, 2022)

Compressed Predictive Information Coding. - Rui Meng; Tianyi Luo; Kristofer E. Bouchard (CoRR, 2022)

FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. - Eliu A. Huerta; Ben Blaiszik; L. Catherine Brinson; Kristofer E. Bouchard; Daniel Diaz 003; Caterina Doglioni; Javier M. Duarte; Murali Emani; Ian T. Foster; Geoffrey C. Fox; Philip C. Harris; Lukas Heinrich; et al. (CoRR, 2022)

Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models. - Alexander Ladd; Kyung Geun Kim; Jan Balewski; Kristofer E. Bouchard; Roy Ben-Shalom (Frontiers Neuroinformatics, 2022)

bids-specification. - Aaron Oliver-Taylor; Adam Li; Adam G. Thomas; Adeen Flinker; Adina S. Wagner; Agah Karakuzu; Aki Nikolaidis; Alberto Lazari; Alejandro de la Vega; Alessio Giacomel; Alexander Rockhill; Alexander Jones; et al. (Zenodo, 2023)

The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies. - Marcin P. Joachimiak; Mark A. Miller; J. Harry Caufield; Ryan Ly; Nomi L. Harris; Andrew J. Tritt; Christopher J. Mungall; Kristofer E. Bouchard (Appl. Ontology, 2024)

Methods for Linking Data to Online Resources and Ontologies with Applications to Neurophysiology. - Matthew Avaylon; Ryan Ly; Andrew J. Tritt; Benjamin K. Dichter; Kristofer E. Bouchard; Christopher J. Mungall; Oliver Rübel (CoRR, 2024)

Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics. - Ankit Kumar; Loren M. Frank; Kristofer E. Bouchard (CoRR, 2024)

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. - Rui Meng; Kristofer E. Bouchard (PLoS Comput. Biol., 2024)

AutoCT: Automated CT registration, segmentation, and quantification. - Zhe Bai; Abdelilah Essiari; Talita Perciano; Kristofer E. Bouchard (SoftwareX, 2024)

Numerical characterization of support recovery in sparse regression with correlated design. - Ankit Kumar; Sharmodeep Bhattacharyya; Kristofer E. Bouchard (Commun. Stat. Simul. Comput., 2024)

The Brain Imaging Data Structure (BIDS) Specification. - Aaron Oliver-Taylor; Adam Li; Adam G. Thomas; Adeen Flinker; Adina S. Wagner; Agah Karakuzu; Aki Nikolaidis; Alberto Lazari; Alejandro de la Vega; Alessio Giacomel; Alexander Rockhill; Alexander Jones; et al. (Zenodo, 2024)

Open-source models for development of data and metadata standards. - Ariel Rokem; Vani Mandava; Nicoleta Cristea; Anshul Tambay; Kristofer E. Bouchard; Carolina Berys-Gonzalez; Andy Connolly (Patterns, 2025)